Agentic knowledge,governedat scale.
Every role.
A different risk.
Every C-suite role carries a different piece of the AI governance risk. Invoked answers each one in their own language. Select your role.
You wouldn't let developers ship codewithout a CI/CD pipeline and a review process.But your AI agents are executing skillswith no equivalent gate —no review, no pipeline, no sign-off.One bad skill, deployed to 100 agents,running 10,000 invocations a day —that's not a mistake.That's a system failure at scale.Invoked is the missing infrastructure.
Your organization's expertise,
encoded as agent skills.
Skills are reusable, file-system-based units of knowledge that equip an agent with domain-specific expertise — the workflows, deep context, and best practices that turn a generalist into a specialist.
Enterprises codify their operational know-how into skills: how Finance processes an invoice, how HR screens a candidate, how Marketing holds a brand voice. That institutional DNA is then deployed across every agent in the fleet — at scale, on demand, without repetition.
Who Can Publish
Right now, anyone in your company can write a skill and every agent in the fleet will run it — no record of who created it, why, or whether it should exist. Invoked is the gate: authoring and publishing locked by role, team, and tier, so only the right people can publish.
Approval Before It Runs
Skills go live the moment someone saves them — no security review, no legal sign-off, no awareness at leadership that it exists until something breaks. Invoked is the checkpoint: every skill enters an approval queue, and security, legal, and domain leads sign off before any agent can invoke it.
Enforced at the Platform
Every skill carries the blind spots of whoever wrote it that day — run across 40 agents, that's not a quality gap, it's a systematic failure. Invoked is the standard: quality, security, and process requirements enforced at the platform, baked in at write time.
One Registry, Full Recall
You can't revoke what you can't find — skills live in repos, Slack threads, and personal laptops with no central inventory and no off switch. Invoked is both: one central registry every agent discovers from, automatically scanned before publish, revoked across the entire fleet in a single action.
Continuous Monitoring
New skills appear in your enterprise repos every day without passing any review — your exposure grows invisibly until it becomes a problem. Invoked is the watchdog: monitoring every repo continuously, surfacing governance gaps, security flaws, duplication, and shadow skills before they reach a single agent.
Agents are the horsepower.
Skills are the harness.
One source of record.
Every agent.
One actionable knowledge base where every skill in your enterprise is authored, reviewed, and approved — and every agent in your fleet discovers what to run.
The exposure is
already there.
One skill library.
Every AI agent.
Skills you author in Invoked run on every AI agent across your enterprise — regardless of model or platform.
When the question comes,
the answer is already there.
When an auditor asks how your AI made a decision — which skill ran, who approved it, what context it had — Invoked already has the answer. Every invocation logged. Every approval recorded. Every skill versioned. The chain of custody your organization needs before anyone asks for it.
Who approved it, and when
Every skill carries a full approval record — who reviewed it, who signed off, and when it went live. When accountability is required, the paper trail is already there.
What standard it was held to
The platform records the version of creation standards applied to every skill. You can show exactly what criteria it was validated against — at the time it was approved.
What it did, and to what
Every invocation logged: which agent, which model, what context, when. Not a black box — a complete record your auditors, regulators, and legal team will ask for.
What you did when you found it
When a skill is found to encode wrong logic or a security flaw, Invoked records the revocation — who triggered it, when, and confirms removal across the entire fleet instantly.
We're building this
with a small group of enterprises.
Not for them. With them.
The enterprises that join us now aren't waiting for a finished product. They're defining what enterprise AI governance looks like at scale — what the approval flow must handle, what the audit trail needs to prove, what revocation feels like across 10,000 agents.
We're selecting a small number of enterprises. Not every applicant will be a fit — and that's intentional.
Scan. Pilot. Scale.
Every design partner follows the same path — not because it's a sales funnel, but because it's the only way to build enterprise governance that actually holds under real conditions.
Scan
Before you can govern it, you need to see it.
Every AI agent discovers skills from a standard path on the device it runs on. We scan only those paths — read-only, no source code access, no repo permissions required. You get a governance gap report: shadow skills, security surface, outdated logic, skills deployed outside any approval process. This report becomes the starting point for the pilot — we use what we find to design your governance architecture together.
Pilot
One team. Full governance. Real signal.
Deploy Invoked with a single team — whichever carries the most risk. Approval workflow, federated authorship, full invocation audit trail, continuous monitoring — live, with your data, in your environment. But more than deployment: this is where your requirements shape the product. Your edge cases become our roadmap. Your compliance constraints become our defaults.
Enterprise
Every team. Every agent. Governed.
Full deployment across every team and department. At this stage, you're not just a customer — you're a reference architecture. The governance framework we built with you becomes the foundation for how Invoked works at scale. Unlimited agents. Compliance and standards at the platform level. SLA, custom contracts, and on-premise deployment available.
Direct influence on the product roadmap
Priority access before general availability
A governance framework built around your enterprise context
From the registry
Frontier AI is a commodity. Company expertise is the moat.
The model your agent uses is the model your competitor's agent uses. The differentiation isn't in the model — it's in what you put on top of it.
Your AI hasn't read the onboarding doc
Engineering standards used to live in Confluence. Now they need to live in your AI.
Auditing agent tool calls in Claude Code
What a thinking trajectory is, and why most agent logging falls short of capturing it.
Find out what your
agents are running.
Every AI agent on your devices discovers skills from a standard path. Invoked reads those paths — nothing else. No source code, no repo access, no permissions beyond what your agents already use.
You get a map of every skill running across your organisation: what it does, who built it, whether it's ever been reviewed. Most enterprises are shocked by what they find.
Read-only. No source code access. No commitment.